AI 中文总结
该研究通过混合方法研究分析18位创作者与16位用户的仪表盘交互序列，梳理出影响阅读顺序的多类因素，识别出阅读模式并探讨相关计算方法的应用机遇。
AI 中文摘要
仪表盘是数据分析中广泛使用的界面，在单个视图内结合了多种可视化内容、文本和交互式控件。尽管仪表盘创作者常通过布局构建逻辑使用流程，但用户对仪表盘的解读与导航方式可能因设计特征、分析目标和个人偏好的相互作用而不同。本研究通过考察用户的阅读顺序（即用户与仪表盘组件交互的序列），探究人们如何理解仪表盘。我们开展了一项混合方法研究，共有18位仪表盘创作者和16位终端用户参与，记录参与者如何设计并思考这些组件间的转换。通过对参与者生成的交互序列进行定性与定量分析，我们梳理出影响仪表盘阅读顺序的一系列因素，包括布局、视觉显著性、语义、功能角色、交互性和用户情境。我们还识别出新兴的阅读模式，并通过聚合与变异性指标对其进行分析，揭示用户解读中的趋同与分歧之处。最后，我们探讨了旨在自动建模、引导或序列化仪表盘使用的计算方法的意义与机遇。
英文摘要
Dashboards are widely used interfaces for data analysis, combining multiple visualizations, text, and interactive controls within a single view. While dashboard authors often structure layouts to suggest a logical consumption flow, users may interpret and navigate dashboards differently depending on the interplay between design features, analytical goals, and personal preferences. In this work, we investigate how people make sense of dashboards by examining their reading orders, i.e., the sequences in which users engage with dashboard components. We conduct a mixed-methods study with 18 dashboard authors and 16 end-users, capturing how participants design for and reason through these component transitions. Through qualitative and quantitative analyses of participant-generated flows, we outline a set of factors that influence dashboard reading order, including layout, visual saliency, semantics, functional roles, interaction, and user context. We also identify emergent reading patterns and analyze them through aggregate and variability measures, revealing where users converge and diverge in their interpretations. Finally, we discuss implications and opportunities for computational approaches that aim to automatically model, guide, or serialize dashboard consumption.
Commentsmain (11 pages) + appendix (5 pages). TVCG, to appear
